Spatial multiplexing of histological stains

ABSTRACT

The following concerns a method for co-localization of microscopy or histology stains by the assembly of a virtual image from one or more imaging operations. In particular, the method decreases the time required to obtain multiple labeled antigen or protein histology images of a biological sample. The method includes imaging the tissue as it is sliced by a microtome with a knife edge scanning microscope and spatially aligning the samples by the generated images. The spatial alignment of samples enabled by the method allows a panel of different antigen or protein secondary or functional stains to be compared across different sample slices, thereby allowing concurrent secondary stains of tissues and cells.

CROSS-REFERENCE

This application claims benefit as a Continuation of U.S. applicationSer. No. 15/205,288, filed Jul. 8, 2016, which claims benefit of U.S.Provisional Application No. 62/190,931, filed Jul. 10, 2015, the entirecontents of the aforementioned is hereby incorporated by reference as iffully set forth herein, under 35 U.S.C. § 120. The applicant(s) herebyrescind any disclaimer of claim scope in the parent application(s) orthe prosecution history thereof and advise the USPTO that the claims inthis application may be broader than any claim in the parentapplication(s).

BACKGROUND

The present disclosure generally relates to a method of slicing,imaging, and staining tissue for diagnostic or research purposes. Inparticular, the present disclosure relates to Serial Section Microscopy,the sectioning of biological tissue and other material samples using amicrotome, and more specifically, a method of imaging tissue samplesstained with immunohistochemical antigens.

Immunohistochemistry is a process in which a set of antigens are appliedto a section of biological tissue. Immunohistochemical staining iscommonly used to identify abnormal cells, employing antibodies to testfor certain antigens in a sample of tissue. The antibody is usuallylinked to a radioactive substance or a dye that causes the antigens inthe tissue to become visible under a microscope, and this process isgenerally done in a panel or series of different stains to detectvarious cancer cell strains.

The present disclosure converges and optimizes of several differentworkflows that are traditionally used in immunohistochemistry by usingthe novel methods and processes made possible with the KESM technology.By presenting the following three studies of traditional workflows thatrepresent the current state of the art, the novel and useful method asdescribed herein can be better understood.

SUMMARY

The present disclosure generally relates to systems and methods for animaging an object with a microtome and applying immunohistochemicalstains, in order to detect certain biological markers for medicaldiagnosis or research. In particular, the present disclosure relates tousing Serial Section Microscopy for these diagnostics, by sectioningbiological tissue and other material samples using a Knife Edge ScanningMicroscope and applying stains to individual sections, and using aspatial multiplexing method enabled by the Knife Edge Scanningtechnology to compare various stains and reactions across a sample.

The following concerns techniques for rapid pathological and/orhistological examination of a tissue sample using multiple contrastingagents. By performing an additional imaging step before tissue handlingmade possible by the Knife Edge Scanning Microscope, the fundamentalshape of the imaged object can be captured before physical or chemicaldeformations are made. Thus, the deformed slice may be registered backinto the original coordinate system of the sample. This can also presenta unique ability to better co-locate biological markers across manyserial sections of a single sample, and can create a more accuraterepresentation of the tissue as a whole by using the intermediateimaging step to re-map individual sections to each other, after chemicalor mechanical treatment. This can provide unique advantages by allowingmultiple contrast agents to be compared quickly across a sample morequickly than the traditional workflow, with less distortions.

Other goals and advantages of the disclosure will be further appreciatedand understood when considered in conjunction with the followingdescription and accompanying drawings. While the following descriptionmay contain specific details describing particular embodiments of thedisclosure, they should not be construed as limitations to the scope ofthe disclosure but rather as an exemplification of preferableembodiments. For each aspect of the disclosure, many variations arepossible as suggested herein that are known to those of ordinary skillin the art. A variety of changes and modifications can be made withinthe scope of the disclosure without departing from the spirit thereof.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present invention will be obtained by reference to thefollowing detailed description that sets forth illustrative embodiments,in which the principles of the invention are utilized, and theaccompanying drawings of which:

FIG. 1A is a schematic illustrating the typical anatomist's workflowusing the current state of the art.

FIG. 1B is a schematic illustrating the typical histologist orpathologist's workflow using the current state of the art.

FIG. 1C is a schematic illustrating the typical biologist's workflowusing the current state of the art.

FIG. 1D1 is a is a schematic illustrating how image distortions occur intraditional workflow using the current state of the art.

FIG. 1D2 is a schematic illustrating how spatially mulitplexing usingthe technology described herein improves the process of aligning imagestacks by aligning to a non-distorted image.

FIG. 2A is a schematic illustrating the steps for imaging a sample usingthe spatial multiplexing method described herein.

FIG. 2B is a schematic illustrating the co-registration of Primary andSecondary Images by side-by-side presentation.

FIG. 2C is a schematic illustrating the co-registration of several Zimages with different stains applied by mathematical combination tocreate a composite image of coincident stain reactions.

DETAILED DESCRIPTION

Improved systems and methods are disclosed herein by comparison to thethree traditional processes of slicing, staining and imaging tissuesamples as described above. The present disclosure includes improvementsupon the three aforementioned workflows by introducing an additionalimaging step(s) at or before the time of sectioning, enabled by the KESMtechnology.

Definitions

“Immunohistochemistry” may refer to the application of antigens orproteins in tissue sections by the use of labeled antibodies as specificreagents that cause antigen-antibody interactions, which can bevisualized by a marker such as fluorescent dye or stain.

“Serial Section Microscopy” may refer to the practice of taking serialsections with a microtome and imaging them, traditionally by mountingthe slices to glass and staining.

“Knife Edge Scanning Microscope” or “KESM” may refer to a microscopethat performs Serial Section Microscopy in an automated fashion. SeeU.S. Pat. No. 6,744,572.

“Section” or “slice” may refer to a single strip of contiguous materialthat was removed from the block face by means of a relative motionbetween the sample and the knife.

“Microtome” may refer to a device in which a block of material isprecisely cut such that a very thin layer of material is removed, orsectioned, from the surface of the block. Similarly, the term“microtomy” may apply to the operation of microtomes.

“Imagery” may include any technique designed to measure an “image”, aspatial map of an optical or electronic response. This can includeoptical or electron microscopy techniques.

“Imaging” may generally refer to data collection in order to generate avisualization of a given area.

“Registration” or “co-registration” may refer to a computational step inwhich images are aligned, stretched, and deformed to match one another.In reference to Serial Sectioning Microscopy, this step can correct fortissue deformation from slicing, mounting, and chemical treatments.

“Multiplex” or “multiplexing” may refer to a method of selecting onelocation within a matrix by having two selective addressing systems onboth sides of the matrix, thus needing only 2N selectors to address NA2locations.

“Stain” may refer to a chemical treatment, which aims to change thephotonic response of all or parts of a medium, by methods including butnot limited to attaching a pigment, a genetically expressed flourophore,or chemistry designed to modify the target structure to be imaged. Thismay include but is not limited to traditional light microscopy stains,contrast agents used in immunohistochemistry (IHC) and in situhybridization (ISH) labeling techniques.

“Molecular Diagnostic” may refer to a form of chemical test or assay,which takes a sample of tissue and identifies biological markers to makea diagnostic.

“Transformation” may refer to the re-mapping of a single point in animage from the unstained image to another stained image.

“Interpolation” may encompass methods for selective spatial sampling ofa numerical value derived from another numerical field. Methods commonlyused may include “nearest-neighbor” interpolation, linear, polynomial,or b-spline based techniques. These are generally used to computediscreet “interpolant” values of a transformed image, or approximate thevalue of a function at a given spatial coordinate.

Distortions

The process of capturing and mounting sections from a microtome to aglass slide may physically distort the tissue. The distortion can be awarping of the thin and delicate tissue, a folding of the sections, oreven tearing. The warping can prevent simple alignment of serialsections, as the microscopic features may not line up properly fromsection to section. Typically, the distortions must be corrected using acombination of manual editing and software, where registration marks arechosen on the adjacent images and software aligns the registrationmarks. This process is often slow and difficult, and can prevent themore widespread adoption of serial sectioning.

Staining and Slice Thickness

Controlling slice thickness can be important for several reasons:

-   -   1. Maintaining the structural/architectural integrity of the        section for subsequent handling, staining, mounting, and        processing.    -   2. Ensuring that the section is an appropriate thickness to the        structures being resolved. The slice should be thick enough so        that unique features fit within the slice. In cell        characterization, the slice is typically a thickness, which        allows 1-2 layers of cells in plane. If it is too thick, many        layers of cells can obscure the ability to obscure cell level        detail. Similarly, if the slice it too thin relevant features        within a singular cell layer may be truncated.    -   3. Ensuring that the slice is thin enough of the chemical        kinetics of staining to adequately label the associated        features. Many contrast agents employ large molecules, which may        be limited in the amount of tissue through which they are able        to diffuse and correspondingly label.

Similarly contrast agents, which can depend on chemical-kinetics of thebase material, may behave differently for thick or thin sections.

It is common practice in histology or pathology labs to cut slices ofdifferent thickness for different staining/contrasting techniques. Thisis especially true when rapid results are needed (thin slices typicallycan be stained more quickly), or complex chemistries are employed in thestaining as in IHC or ISH methods.

The Anatomist Workflow

There are many reasons that a biologist might want to measure a tissueproperty across a three dimensional volume of space. To do this usingthe current state of the art, several slices would be cut, stained, andco-registered against one and other. FIG. 1A is a diagram thatillustrates the typical anatomist's workflow 100A employing the currentstate of the art. In a step 111, a sample 101 may be sliced into one ormore thick sections such as a first thick section 121A, a second thicksection 121B, and a third thick section 121B. The thick sections 121A,121B, 121C may be stained in a step 131 and the stained thick sections121A, 121B, 121C may then be imaged and co-registered with one anotherin a step 141.

The Histologist/Pathologist Workflow

Similarly, when a histologist or pathologist is attempting to make adiagnosis of diseased tissue, several thick sections 121A, 121B, 121Cmay be cut. Then, one would be stained, imaged and examined in a step151. Based on the imagery input from a medical professional, thisprocess could be repeated several times before finally a diagnosis ismade in a step 161, and the diagnosis of one of the thick sections maybe used to inform the staining, imaging, and examination of furtherthick sections. The diagnosis of the stained thick sections may indicatean appropriate treatment for the patient in a step 171. FIG. 1B is adiagram that illustrates the typical histologist or pathologist'sworkflow 100B employing the current state of the art.

The Biologist Workflow

Biological researchers typically employ an immunohistochemical stainingtechnique where a particular piece of tissue is stained, imaged, thenstripped clear of the stain from the section of tissue. The staining andstripping process can be repeated in order to image the immune orantigen reactions of a full panel of stains on the sample piece oftissue. FIG. 1C is a diagram that illustrates the typical biologist'sworkflow 100C employing the current state of the art. The sample 101 canbe sliced and placed in a slide in a step 181. In a step 191, theslice/slide may be stained. In a step 1011, the stained slide/slice maybe imaged. In a step 1031, the image may be stored. In a step 1021, thestain may be removed and the slide/slice may be stained once more in astep 191.

This process of putting down a stain, imaging, stripping the stain,re-staining, re-imaging the stain, then re-imaging again is known asserial multiplexing. This approach, which is commonly used by biologistsin immunohistochemistry, is time consuming, often taking a week orlonger to complete a full panel of antigen stains.

Another approach is differential staining of the next section, based onexamination from a pathologist. This can lead to fairly long turnaroundtimes, as well as needing increased interaction from the physician.

All of these approaches have fundamental drawbacks which the scope ofthis disclosure seeks to address:

-   -   The slide-mounting, staining, and imaging each introduce unique        deformations, distortions, and artifacts in the slices which can        make the final process of co-registration difficult, error        prone, and time consuming.    -   There are often a large number of serial steps, each of which        can involve significant human labor and attention to detail if        high-quality reliable results are to be produced.    -   Given the 3D nature of a sample, the features can be changing        across even adjacent slices, and automated feature extraction        and warp correction has been difficult in larger samples.

The present disclosure describes systems and methods to decreases thehuman effort required to process multiple stains on a sample andincrease the accuracy of the reconstructed products by introducing anadditional imaging step enabled by the KESM technology as appliedherein.

Post-Processing Distortions

In typical serial section microscopy, the slices are aligned using humanannotation or algorithms, where the warping during mounting is correctedprior to reconstructions. The process typically involves the selectionof registration marks, which are points that occur across adjacentsections. The registration points may be used to calculate atransformation function, which is applied to both images to bring thepixels in the images into alignment. Choosing registration marks acrossa series of images can be difficult, because each of the images in thestack is different from the next. Features also rarely cross exactlyperpendicular to the cutting plane, so if the same features are chosenfor registration marks, the features may drift spatially across thesections and thus for example an object at an incline may bemisconstrued as being vertical.

As disclosed herein, the post-processing of images may be improvedbecause the post-processing of distortions may be performed on twoimages of the exact same section, one without distortions and one ormore without. Since the images are of the same slice, the same exactregistration marks will occur on all images, making the selectionprocess easier and more consistent. The same phenomenon can also reducespatial drift that would otherwise occur for cylindrical featurestraveling at an incline relative to the cutting plane. FIG. 1D1 and FIG.1D2 illustrate how distortions occur employing the current state of theart (FIG. 1D1) in comparison to how image post-processing may beimproved with regard to these distortions as disclosed herein (FIG.1D2).

As shown in FIG. 1D1, an object 103 may be in present in the sample 101which may be sliced into two slices 105A and 105B. Images 107A, 107B maybe generated for each slice 105A, 105B, respectively, showing the object103 at different depths.

As shown in FIG. 1D2, an object 103 may be present in the sample 101which may be sliced into two slices 105A and 105B. Primary and secondaryimages may be generated for each of the slices 105A, 105B (such asprimary image 109A1 and secondary image 109A2 for primary slice 105A,and primary image 109B1 and secondary image 109B2 for secondary slice105B.)

Primary Imaging

As described herein, the first step in this method comprises a PrimaryImaging (PI) step, which may capture a view of the section beforeprocessing or post-processing distortions. This may be accomplished byimaging the sample before slicing or by imaging during slicing. Theprimary imaging may be performed with a KESM, which may capture anun-warped image on the block face during the slicing operation. Theseimages may be referred to as X_N. By incorporating this PI step, theSecondary Imaging (SI) step can have a direct anchor to the actualoriginal shape and location of the slice, which may enable betterregistration and analysis of stain reactions of a sample. FIG. 2A is adiagram that illustrates the imaging steps for the spatial multiplexingmethod 200. The sample 101 may be imaged in a primary imaging step 211Abefore a thin section 221A is sliced from the sample 101. Furtherprimary imaging steps 211B to 211N may be performed before furtherslicing the sample to further thin sections 221B to 221N. The primaryimages may be collected and registered with one another to generate avirtual thick slice 223.

As described herein, after the PI steps (221A, 221B, . . . 221N), theslice(s) may be mounted on a glass slide and antigen or protein stainsmay then be applied in a step 231 to the sample slices for furtheranalysis.

Secondary Imaging

Another aspect of the disclosure includes a Secondary Imaging (SI)step(s) 241A, 241B, . . . 241N. In the SI steps, the KESM may be used toimage the stained slices of the sample 101 after a stain or a full panelof stains 231 has been applied. These step(s) may be repeated as manytimes as is desired, re-imaging the slices each time a new stain isapplied to the sample. These images will be referred to as Y_n.

Reconstruction

Another aspect of the disclosure describes a reconstruction step. In thereconstruction step, various computations may be employed to create areconstructed image across different stained images. As shown in FIG.2A, the secondary images may be collected and registered with oneanother to generate a stack of co-registered stains 243. The primaryvirtual thick slice 223 and the co-registered stack of stained slices242 may be analyzed in a data-gathering or diagnosis step 251.

As described herein, a computational transformation of the Y_n imagesmay be performed to reconstruct and spatially align the various sampleslices to each other. The panel of stained Y_n images may be mapped backto the biomarker coordinates established by the X_n images by employingcomputational transformations. These remapped images will be referred toas Z_n. These computational transformations may include, but are notlimited to:

-   -   a. “Procrustean” transformations, which may include stretch,        shear, translation, rotation, and more general affine        transformations to map visible variables or biomarkers across        images.    -   b. “Elastic sheet” type transformations employing basis splines,        or other non-linear interpolation schemes to map biomarkers by        matching the curvature of the object, incorporating both affine        and nonaffine transformations.    -   c. Optical-based corrections to account for the differences        between the optics of the primary and secondary imaging. This        can include perspective, barrel, pincushion, and chromatic        corrections.

Co-Registration

Another aspect of the disclosure describes a co-registration step,wherein the images from the PI and SI steps captured by the KESM arecompared and aligned to each other based on the mapped biomarkersestablished in the reconstruction step.

As described herein, the stack of Z_n images may be superimposed toco-register the different stains. This step may be repeated to completea full panel of stains and compare the results based on theco-registered images. Methods for completing the co-registration stepmay include:

-   -   a. Side-by-side presentation, rendering, or image overlay of the        Z_n images. FIG. 2B illustrates how the Primary images 261 and        Secondary images 262 are co-registered using a side-by-side        presentation method, and may be shown as a composite image 263.    -   b. Mathematical combination of several Z images to create a        composite image or virtual “slice” capable of showing where        different stains are present, and/or coincident. FIG. 2C        illustrates how several images 271, 272, 273 may be combined to        create a composite image 274 by mathematic combination.

Further Embodiments

An additional embodiment of a workflow may be similar to the work flow200 above, with an additional imaging step between the mounting andstaining steps.

The above description(s) describes the treatment of a single slice inFIG. 2A. Using the primary imaging information, multiple slices may bealigned across the Z plane to the slices above and below within thesample. Using this anchoring, the workflows 100A, 100B, 100C describedabove may be replaced in the following ways:

-   -   The Anatomist Workflow 100A: All of the stains in the        “stain-panel” can be made the same. Each stained slice may be        linked back to its primary imaging, and the primary images to        each other. This can both improve the quality of reconstruction,        as well as minimize the fraction of human involvement.    -   The Histologist/Pathologist Workflow 100B: A large number of        requested stains could be run independently within the panel.        Each of these stained images may be again linked back to the        primary imaging, and many layers/contrast agents may be linked        back to the overall sample. This may minimize the number of        iterations in which the medical professional would be involved,        and lead to a quicker diagnosis, and faster turnaround on lab        analyses.    -   The Biologist Workflow 100C: Several different stains could be        repeated on interleaved layers. In this way stains could be        multiplexed over the sample volume, and example including 3        stains labeled a, b, c might look like:        -   a|b|c|a|b|c|a|b|c|a|b|c|a|b|c|a|b|c

This multiplexing approach gives a larger 3D distribution of the labelsacross the volume while tethering each slice back to the overall block.Additionally, the stained information could be interpolated acrossadjacent sections.

These embodiments could also be augmented in any one of at least thefollowing ways:

-   -   1. Several channel images can be combined into one, creating a        virtual multi-channel panel image    -   2. The optimal sectioning thickness and number of stains can be        determined by the features observed in the primary imaging, i.e.        some features may be large, and thick sections may be        appropriate, where other features are smaller and may        necessitate thin sections.    -   3. The entire panel does not have to be determined at once. The        output of a first round of imaging could be used to determine        the second round.    -   4. Section thickness could be adjusted with respect to the stain        chemistry, i.e. thinner or thicker sections can be cut for a        multiplexed stain optimized for each particular contrast agent's        properties.    -   5. Every n'th slice might be treated differently, based on the        primary imaging. This might include:    -   6. Being sliced at a thickness optimal for the stain in        question.    -   7. Being diverted to a molecular diagnostic or other chemical        assay.    -   8. Be discarded based on an imaging or slicing defect or lack of        sample in the slice.    -   9. Be archived to comply with regulations.    -   10. As above, but instead making the slice treatment decision        based on the Primary Imaging step.

While preferred embodiments of the present disclosure have been shownand described herein, it will be obvious to those skilled in the artthat such embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the scope of the present disclosure.It should be understood that various alternatives to the embodiments ofthe present disclosure described herein may be employed in practicingthe inventions of the present disclosure. It is intended that thefollowing claims define the scope of the invention and that methods andstructures within the scope of these claims and their equivalents becovered thereby.

What is claimed is:
 1. A method of analyzing a sample, the methodcomprising: slicing the sample into a plurality of sections; for eachsection in the plurality of sections: generating a primary image of thesection; associating the primary image with the section; based oninformation from the primary image of the section, determining whetherto stain the section; based on a determination that the section is to bestained: determining a staining agent to be used to stain the sectionusing the information from the primary image of the section; stainingthe section using the staining agent; generating a secondary image ofthe section by imaging the stained section; and associating thesecondary image with the section.
 2. The method of claim 1, wherein thesample comprises a tissue sample.
 3. The method of claim 1, furthercomprising: for each section in the plurality of sections having anassociated primary image and an associated secondary image:co-registering the associated primary image with the associatedsecondary image by post-processing the associated primary image havingno distortions with the associated secondary image having distortionsthat occurred during the staining, thereby improving post-processing ofimages; and wherein the post-processing includes processing distortionsin the associated secondary image based on the associated primary image;and co-registering the secondary images associated with the plurality ofsections with one another.
 4. The method of claim 1, further comprising:generating a virtual model of the sample based on primary imagesassociated with each section of the plurality of sections.
 5. The methodof claim 1, further comprising: for each section in the plurality ofsections having an associated primary image and an associated secondaryimage: co-registering the associated primary image with the associatedsecondary image by post-processing the associated primary image havingno distortions with the associated secondary image having distortionsthat occurred during the staining, thereby improving post-processing ofimages; and wherein the post-processing includes processing distortionsin the associated secondary image based on the associated primary image;co-registering the secondary images associated with the plurality ofsections with one another; and co-registering the co-registeredplurality of secondary images of the sample to the virtual model.
 6. Themethod of claim 5, further comprising: generating a diagnosis inresponse to the co-registration of the co-registered plurality ofsecondary images of the sample and the virtual model.
 7. The method ofclaim 1, wherein slicing the sample into a plurality of sectionscomprises slicing a block face of the sample.
 8. The method of claim 1,further comprising: mounting the plurality of sections onto a pluralityof slides.
 9. The method of claim 1, wherein the staining agent is oneof: an antigen or protein stain.
 10. One or more non-transitorycomputer-readable storage media, storing one or more sequences ofinstructions, which when executed by one or more processors causeperformance of: slicing the sample into a plurality of sections; foreach section in the plurality of sections: generating a primary image ofthe section; associating the primary image with the section; based oninformation from the primary image of the section, determining whetherto stain the section; based on a determination that the section is to bestained: determining a staining agent to be used to stain the sectionusing the information from the primary image of the section; stainingthe section using the staining agent; generating a secondary image ofthe section by imaging the stained section; and associating thesecondary image with the section.
 11. The one or more non-transitorycomputer-readable storage media of claim 10, wherein the samplecomprises a tissue sample.
 12. The one or more non-transitorycomputer-readable storage media of claim 10, further comprising: foreach section in the plurality of sections having an associated primaryimage and an associated secondary image: co-registering the associatedprimary image with the associated secondary image by post-processing theassociated primary image having no distortions with the associatedsecondary image having distortions that occurred during the staining,thereby improving post-processing of images; and wherein thepost-processing includes processing distortions in the associatedsecondary image based on the associated primary image; andco-registering the secondary images associated with the plurality ofsections with one another.
 13. The one or more non-transitorycomputer-readable storage media of claim 10, further comprising:generating a virtual model of the sample based on primary imagesassociated with each section of the plurality of sections.
 14. The oneor more non-transitory computer-readable storage media of claim 10,further comprising: for each section in the plurality of sections havingan associated primary image and an associated secondary image:co-registering the associated primary image with the associatedsecondary image by post-processing the associated primary image havingno distortions with the associated secondary image having distortionsthat occurred during the staining, thereby improving post-processing ofimages; and wherein the post-processing includes processing distortionsin the associated secondary image based on the associated primary image;co-registering the secondary images associated with the plurality ofsections with one another; and co-registering the co-registeredplurality of secondary images of the sample to the virtual model. 15.The one or more non-transitory computer-readable storage media of claim14, further comprising generating a diagnosis in response to theco-registration of the co-registered plurality of secondary images ofthe sample and the virtual model.
 16. The one or more non-transitorycomputer-readable storage media of claim 10, wherein slicing the sampleinto a plurality of sections comprises slicing a block face of thesample.
 17. The one or more non-transitory computer-readable storagemedia of claim 10, further comprising: mounting the plurality ofsections onto a plurality of slides.
 18. The one or more non-transitorycomputer-readable storage media of claim 10, wherein the staining agentis one of: an antigen or protein stain.
 19. A method of analyzing asample, the method comprising: slicing the sample into a plurality ofsections; for each section in the plurality of sections: generating aprimary image of the section; associating the primary image with thesection; and based on information from the primary image of the section,diverting the section to a molecular diagnostic.